CN112434975A - Digital supervision method and system for oil discharge operation process of gas station - Google Patents
Digital supervision method and system for oil discharge operation process of gas station Download PDFInfo
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Abstract
The invention provides a digital supervision method for the oil discharge process of a gas station, which comprises the steps of receiving a real-time image of an oil discharge vehicle before the oil discharge operation of the gas station and a real-time image of each specified target object outside the oil discharge vehicle, detecting whether the oil discharge operation is ready or not by combining a preset automatic identification model group, and further sending an oil discharge operation command to field personnel after detecting that the oil discharge operation is ready; receiving real-time operation images of field personnel, receiving real-time images of all specified target objects in the oil unloading operation after the oil unloading operation task is determined to be started, further utilizing a preset automatic identification model group to perform follow-up analysis on the received real-time images of all specified target objects in the oil unloading operation, and determining whether the oil unloading operation is safe or not according to an analysis result. The invention can monitor the improper behavior of the oil discharge operation of the gas station in real time and can effectively reduce the occurrence of safety accidents in the oil discharge operation process.
Description
Technical Field
The invention relates to the technical field of gas station safety supervision, in particular to a digital supervision method and system for a gas station oil discharge operation process.
Background
At present, most of various potential safety hazards existing in oil discharge operation of a gas station depend on-site supervision of workers to check. However, the necessary steps and misbehaviour of some oil-discharge operations are easily overlooked, and this is precisely the main cause of accidents in oil-discharge operations at filling stations.
Therefore, in order to solve the above problems, a perfect supervision system is needed to supervise the oil unloading operation process of the gas station, and the improper behavior of the oil unloading operation of the gas station can be monitored in real time, so that the safety accidents in the oil unloading operation process can be effectively reduced.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide a method and a system for digitally supervising the oil discharge process of a gas station, which can monitor the improper behavior of the oil discharge operation of the gas station in real time and effectively reduce the occurrence of safety accidents in the oil discharge process.
In order to solve the technical problem, an embodiment of the present invention provides a digital supervision method for a fuel discharge process of a gas station, including the following steps:
s1, receiving the real-time images of the oil unloading vehicle before oil unloading operation of the gas station and the real-time images of other specified objects, detecting whether the oil unloading operation is ready or not by combining a preset automatic identification model group, and further sending an oil unloading operation command to field personnel after detecting that the oil unloading operation is ready; the specified target object comprises an electrostatic identification, a fire-fighting device, an oil discharge port cover and an oil discharge pipeline;
and S2, receiving the real-time operation images of the field personnel, receiving the real-time images of the specified target objects in the oil unloading operation after the oil unloading operation task is determined to be started according to the real-time operation images of the field personnel, further utilizing the preset automatic identification model group to perform follow-up analysis on the received real-time images of the specified target objects in the oil unloading operation, and determining whether the oil unloading operation is safe or not according to the analysis result.
Wherein, the step S1 specifically includes:
receiving real-time images of the oil unloading vehicles before oil unloading operation of the gas station, and receiving real-time images of all specified target objects except the oil unloading vehicles;
the method comprises the steps of using a preset first automatic identification model to carry out vehicle identification on a real-time image of an oil unloading vehicle before oil unloading operation of a gas station, using a preset second automatic identification model to carry out position identification on a real-time image of an electrostatic identification before the oil unloading operation of the gas station when the oil unloading vehicle is identified to be a vehicle meeting a preset condition, using a preset third automatic identification model to carry out position identification on a real-time image of an oil unloading cover before the oil unloading operation of the gas station, using a preset fourth automatic identification model to carry out position identification on a real-time image of fire fighting equipment before the oil unloading operation of the gas station, and using a preset fifth automatic identification model to carry out position identification on a real-time image of an oil unloading pipeline before the oil unloading operation of the gas station;
and if the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline are identified to respectively and correspondingly reach the preset positions before the oil discharge operation, determining that the oil discharge operation is ready, and sending an oil discharge operation command to field personnel.
Wherein, the step S2 specifically includes:
receiving a real-time operation image of a field worker;
performing action recognition on the real-time operation image of the field personnel by using a preset sixth automatic recognition model, and determining to start an oil unloading operation task after recognizing that the real-time operation image of the field personnel meets a preset action condition;
receiving real-time images of each specified target object in oil unloading operation, wherein the real-time images comprise an electrostatic identification real-time image, an oil unloading opening cover real-time image, a fire-fighting equipment real-time image and an oil unloading pipeline real-time image which are contained in the oil unloading operation of a gas station;
the preset second automatic identification model is used for carrying out position identification on the static identification real-time image in the oil unloading operation of the gas station, the preset third automatic identification model is used for carrying out position identification on the oil unloading cover real-time image in the oil unloading operation of the gas station, the preset fourth automatic identification model is used for carrying out position identification on the fire-fighting equipment real-time image in the oil unloading operation of the gas station, and the preset fifth automatic identification model is used for carrying out position identification on the oil unloading pipeline real-time image in the oil unloading operation of the gas station;
if at least one of the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline is not in the preset position area in the corresponding oil discharge operation at a certain moment, the unsafe oil discharge operation is determined;
otherwise, if the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline are all recognized to be always in the preset position area in the oil discharge operation, the oil discharge operation safety is determined.
Wherein the method further comprises:
and if the oil unloading operation is determined to be unsafe, an alarm is given.
Wherein the method further comprises:
and receiving a real-time image of the oil discharge area of the gas station vehicle, and detecting whether the oil discharge area of the gas station vehicle contains an illegal vehicle or not by combining a preset oil discharge time range.
The method comprises the following specific steps of receiving a real-time image of a fuel discharge area of a gas station vehicle, and detecting whether the fuel discharge area of the gas station vehicle contains an illegal vehicle or not by combining a preset fuel discharge time range:
in the real-time image of the oil unloading area of the gas station vehicle, a preset oil unloading time range is taken as an intercepting time period, images in the period of the non-oil unloading task outside the preset oil unloading time range are reserved, when the vehicle appears in the images in the period of the non-oil unloading task, the fact that the vehicle is parked illegally is determined, and further an alarm is given out.
Wherein, before the step S1, the method further comprises the steps of:
the method comprises the steps that field personnel log in and apply for oil discharge operation through mobile phone apps, and the login account and the password are newly added in a preset user login interface, oil discharge information is created in a preset oil discharge task interface, oil discharge tasks are newly added in a preset task list interface, and all historical oil discharge tasks and corresponding states are inquired.
The oil unloading information comprises oil unloading time, oil unloading state, license plate numbers of the front and the back of the oil unloading vehicle, driver identity information of the oil unloading vehicle and safety personnel identity information of a gas station.
The embodiment of the invention also provides a digital supervision system for the oil discharge operation process of the gas station, which comprises an information supervision unit before oil discharge operation and an information supervision unit in the oil discharge operation; wherein,
the pre-oil-discharge operation information monitoring unit is used for receiving the real-time images of the oil-discharge vehicles before the oil-discharge operation of the gas station and the real-time images of all the specified objects except the oil-discharge vehicles, detecting whether the oil-discharge operation is ready or not by combining a preset automatic identification model group, and further sending an oil-discharge operation command to field personnel after detecting that the oil-discharge operation is ready; the specified target object comprises an electrostatic identification, a fire-fighting device, an oil discharge port cover and an oil discharge pipeline;
the oil unloading operation middle information monitoring unit is used for receiving the real-time operation images of the field personnel, receiving the real-time images of the specified target objects in the oil unloading operation after the oil unloading operation task is determined to be started according to the real-time operation images of the field personnel, further utilizing the preset automatic identification model group to perform follow-up analysis on the received real-time images of the specified target objects in the oil unloading operation, and determining whether the oil unloading operation is safe or not according to the analysis result.
The real-time images of the oil unloading vehicles before the oil unloading operation of the gas station and the real-time images of all the other specified objects, as well as the real-time images of the field personnel in the oil unloading operation of the gas station, the real-time images of the oil unloading vehicles and the real-time images of all the other specified objects are acquired by a plurality of cameras arranged around the gas station.
The embodiment of the invention has the following beneficial effects:
the invention identifies the real-time images of the oil unloading vehicles and the real-time images of all specified objects before and during the oil unloading operation through the preset automatic identification model group so as to realize information supervision, can monitor the improper behavior of the oil unloading operation of a gas station in real time and can effectively reduce the occurrence of safety accidents in the oil unloading operation process.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is within the scope of the present invention for those skilled in the art to obtain other drawings based on the drawings without inventive exercise.
FIG. 1 is a flow chart of a digital monitoring method for a fuel discharge operation process of a gas station according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a digital supervision system for a fuel discharge process of a gas station according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, in an embodiment of the present invention, a digital supervision method for a fuel discharge process of a gas station is provided, the method includes the following steps:
step S1, receiving the real-time images of the oil unloading vehicle before oil unloading operation of the gas station and the real-time images of all other specified objects, combining with a preset automatic identification model group to detect whether the oil unloading operation is ready, and further sending an oil unloading operation command to field personnel after detecting that the oil unloading operation is ready; the specified target object comprises an electrostatic identification, a fire-fighting device, an oil discharge port cover and an oil discharge pipeline;
and step S2, receiving the real-time operation images of the field personnel, receiving the real-time images of the specified target objects in the oil unloading operation after the oil unloading operation task is determined to be started according to the real-time operation images of the field personnel, further utilizing the preset automatic identification model group to perform follow-up analysis on the received real-time images of the specified target objects in the oil unloading operation, and determining whether the oil unloading operation is safe or not according to the analysis result.
Before step S1, a plurality of cameras are installed around the gas station to acquire related images in the gas station, including but not limited to real-time images of the oil discharge vehicle, the field personnel, the electrostatic identification, the fire fighting equipment, the oil discharge port cover, the oil discharge pipeline, and the like. Meanwhile, all the cameras and the background supervision platform equipment realize data communication, namely, managers can monitor the gas station in real time through the background supervision platform equipment. In addition, monitoring management software is pre-installed on the background monitoring platform, so that field personnel can log in and apply for oil discharge operation through mobile phone apps, login account numbers and passwords are newly added in a preset user login interface, oil discharge information is created in a preset oil discharge task interface, oil discharge tasks are newly added in a preset task list interface, and all historical oil discharge tasks and corresponding states are inquired. The oil discharge information includes, but is not limited to, oil discharge time, oil discharge state, license plate numbers before and after the oil discharge vehicle, driver identity information of the oil discharge vehicle, and security personnel identity information of a gas station.
In step S1, the background surveillance platform device establishes data communication with a plurality of cameras installed around the gasoline station. Firstly, the background supervision platform equipment receives real-time images of the oil discharge vehicles before the oil discharge operation of the gas station, which are acquired by the camera, and receives real-time images of all specified targets except the oil discharge vehicles before the oil discharge operation of the gas station, which are acquired by the camera.
Secondly, using a preset first automatic identification model to perform vehicle identification on the real-time image of the oil unloading vehicle before the oil unloading operation of the gas station, using a preset second automatic identification model to perform position identification on the real-time image of the electrostatic identification before the oil unloading operation of the gas station when the oil unloading vehicle is identified to be the vehicle meeting the preset conditions (such as detection through license plate consistency matching), using a preset third automatic identification model to perform position identification on the real-time image of the oil unloading cover before the oil unloading operation of the gas station, using a preset fourth automatic identification model to perform position identification on the real-time image of the fire fighting equipment before the oil unloading operation of the gas station, and using a preset fifth automatic identification model to perform position identification on the real-time image of the oil unloading pipeline before the oil unloading operation of the gas station.
And finally, if the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline are identified to respectively and correspondingly reach the preset positions before the oil discharge operation, the oil discharge operation is determined to be ready, and an oil discharge operation command is sent to field personnel. It can be understood that before the oil unloading operation, the electrostatic identification, the oil unloading opening cover, the fire-fighting equipment and the oil unloading pipeline are preset with corresponding positions correspondingly, and once all the positions are met, the oil unloading operation can be prepared.
It should be noted that the background supervision platform device trains an automatic identification model group, which is a pre-trained automatic identification model group by a deep learning method, namely, trains target objects such as oil discharge vehicles, fire fighting equipment, field personnel, electrostatic identifications, oil discharge covers and the like into an automatic identification model.
In step S2, first, the background supervisory platform device receives the live work image of the field personnel.
And secondly, performing action recognition on the real-time operation image of the field personnel by using a preset sixth automatic recognition model, and determining to start the oil unloading operation task after recognizing that the real-time operation image of the field personnel meets the preset action condition. It should be noted that the sixth automatic recognition model may recognize the work trajectory of the field staff from the live working image of the field staff, and determine whether the predetermined action condition is satisfied (i.e., the oil discharge working action is decomposed) using the recognized work trajectory, thereby determining whether the oil discharge working task is started. In addition, before the oil unloading task is started, static electricity needs to be discharged for a certain time (such as 15 minutes) to ensure safety.
And then, receiving real-time images of each specified target object in the oil unloading operation, wherein the real-time images comprise the static mark real-time image, the oil unloading opening cover real-time image, the fire-fighting equipment real-time image and the oil unloading pipeline real-time image which are contained in the oil unloading operation of the gas station.
Then, the preset second automatic recognition model is used for carrying out position recognition on the static mark real-time image in the oil unloading operation of the gas station, the preset third automatic recognition model is used for carrying out position recognition on the oil unloading cover real-time image in the oil unloading operation of the gas station, the preset fourth automatic recognition model is used for carrying out position recognition on the fire fighting equipment real-time image in the oil unloading operation of the gas station, and the preset fifth automatic recognition model is used for carrying out position recognition on the oil unloading pipeline real-time image in the oil unloading operation of the gas station.
Finally, if at least one of the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline is identified not to be in a preset position area in the corresponding oil discharge operation at a certain moment, the oil discharge operation is determined to be unsafe, and an alarm is given out when the oil discharge operation is determined to be unsafe; otherwise, if the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline are all recognized to be always in the preset position area in the oil discharge operation, the oil discharge operation safety is determined.
It should be noted that, since the positions of some designated objects may change during the oil unloading operation, it can be determined whether the oil unloading operation is safe as long as the designated objects are determined to be present in the respective preset position areas all the time or not at a certain moment.
It is understood that the oil discharge vehicle is out of the field, which means that the oil discharge is finished, i.e. the detection of the oil discharge task is finished.
In the embodiment of the invention, whether the vehicle illegally stops in the oil unloading operation area can be detected. Therefore, the method can receive the real-time image of the fuel discharge area of the gas station vehicle, and detect whether the fuel discharge area of the gas station vehicle contains the illegal vehicle or not by combining the preset fuel discharge time range, and the method specifically comprises the following steps:
in the real-time image of the oil unloading area of the gas station vehicle, a preset oil unloading time range is taken as an intercepting time period, images in the period of the non-oil unloading task outside the preset oil unloading time range are reserved, when the vehicle appears in the images in the period of the non-oil unloading task, the fact that the vehicle is parked illegally is determined, and further an alarm is given out.
As shown in fig. 2, in an embodiment of the present invention, a digital supervision system for a fuel discharge process of a gas station is provided, which includes an information supervision unit 110 before fuel discharge and an information supervision unit 120 during fuel discharge; wherein,
the pre-oil-discharge operation information monitoring unit 110 is configured to receive a real-time image of an oil-discharge vehicle before oil-discharge operation of a gas station and a real-time image of each specified target object outside the oil-discharge vehicle, detect whether oil-discharge operation is ready by combining a preset automatic identification model set, and further send an oil-discharge operation command to field personnel after detecting that oil-discharge operation is ready; the specified target object comprises an electrostatic identification, a fire-fighting device, an oil discharge port cover and an oil discharge pipeline;
the oil unloading operation middle information monitoring unit 120 is configured to receive a field personnel real-time operation image, receive a real-time image of each specified target object in the oil unloading operation after an oil unloading operation task is determined to be started according to the field personnel real-time operation image, further perform follow-up analysis on the received real-time image of each specified target object in the oil unloading operation by using the preset automatic identification model group, and determine whether the oil unloading operation is safe according to an analysis result.
The real-time images of the oil unloading vehicles before the oil unloading operation of the gas station and the real-time images of all the other specified objects, as well as the real-time images of the field personnel in the oil unloading operation of the gas station, the real-time images of the oil unloading vehicles and the real-time images of all the other specified objects are acquired by a plurality of cameras arranged around the gas station.
The embodiment of the invention has the following beneficial effects:
the invention identifies the real-time images of the oil unloading vehicles and the real-time images of all specified objects before and during the oil unloading operation through the preset automatic identification model group so as to realize information supervision, can monitor the improper behavior of the oil unloading operation of a gas station in real time and can effectively reduce the occurrence of safety accidents in the oil unloading operation process.
It should be noted that, in the above system embodiment, each included unit is only divided according to functional logic, but is not limited to the above division as long as the corresponding function can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by relevant hardware instructed by a program, and the program may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (10)
1. A digital supervision method for the oil discharge operation process of a gas station is characterized by comprising the following steps:
s1, receiving the real-time images of the oil unloading vehicle before oil unloading operation of the gas station and the real-time images of other specified objects, detecting whether the oil unloading operation is ready or not by combining a preset automatic identification model group, and further sending an oil unloading operation command to field personnel after detecting that the oil unloading operation is ready; the specified target object comprises an electrostatic identification, a fire-fighting device, an oil discharge port cover and an oil discharge pipeline;
and S2, receiving the real-time operation images of the field personnel, receiving the real-time images of the specified target objects in the oil unloading operation after the oil unloading operation task is determined to be started according to the real-time operation images of the field personnel, further utilizing the preset automatic identification model group to perform follow-up analysis on the received real-time images of the specified target objects in the oil unloading operation, and determining whether the oil unloading operation is safe or not according to the analysis result.
2. The digital supervision method for the oil unloading process of the filling station as claimed in claim 1, wherein said step S1 specifically comprises:
receiving real-time images of the oil unloading vehicles before oil unloading operation of the gas station, and receiving real-time images of all specified target objects except the oil unloading vehicles;
the method comprises the steps of using a preset first automatic identification model to carry out vehicle identification on a real-time image of an oil unloading vehicle before oil unloading operation of a gas station, using a preset second automatic identification model to carry out position identification on a real-time image of an electrostatic identification before the oil unloading operation of the gas station when the oil unloading vehicle is identified to be a vehicle meeting a preset condition, using a preset third automatic identification model to carry out position identification on a real-time image of an oil unloading cover before the oil unloading operation of the gas station, using a preset fourth automatic identification model to carry out position identification on a real-time image of fire fighting equipment before the oil unloading operation of the gas station, and using a preset fifth automatic identification model to carry out position identification on a real-time image of an oil unloading pipeline before the oil unloading operation of the gas station;
and if the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline are identified to respectively and correspondingly reach the preset positions before the oil discharge operation, determining that the oil discharge operation is ready, and sending an oil discharge operation command to field personnel.
3. The digital supervision method for the oil unloading process of the filling station as claimed in claim 2, wherein said step S2 specifically comprises:
receiving a real-time operation image of a field worker;
performing action recognition on the real-time operation image of the field personnel by using a preset sixth automatic recognition model, and determining to start an oil unloading operation task after recognizing that the real-time operation image of the field personnel meets a preset action condition;
receiving real-time images of each specified target object in oil unloading operation, wherein the real-time images comprise an electrostatic identification real-time image, an oil unloading opening cover real-time image, a fire-fighting equipment real-time image and an oil unloading pipeline real-time image which are contained in the oil unloading operation of a gas station;
the preset second automatic identification model is used for carrying out position identification on the static identification real-time image in the oil unloading operation of the gas station, the preset third automatic identification model is used for carrying out position identification on the oil unloading cover real-time image in the oil unloading operation of the gas station, the preset fourth automatic identification model is used for carrying out position identification on the fire-fighting equipment real-time image in the oil unloading operation of the gas station, and the preset fifth automatic identification model is used for carrying out position identification on the oil unloading pipeline real-time image in the oil unloading operation of the gas station;
if at least one of the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline is not in the preset position area in the corresponding oil discharge operation at a certain moment, the unsafe oil discharge operation is determined;
otherwise, if the electrostatic identification, the oil discharge port cover, the fire-fighting equipment and the oil discharge pipeline are all recognized to be always in the preset position area in the oil discharge operation, the oil discharge operation safety is determined.
4. The method for digitally supervising the process of a gas station fuel discharge operation as recited in claim 3, wherein said method further comprises:
and if the oil unloading operation is determined to be unsafe, an alarm is given.
5. The method for digitally supervising the process of fuel discharge operations at a gasoline station as claimed in claim 1, wherein said method further comprises:
and receiving a real-time image of the oil discharge area of the gas station vehicle, and detecting whether the oil discharge area of the gas station vehicle contains an illegal vehicle or not by combining a preset oil discharge time range.
6. The digital supervision method for the fuel discharge process of the gasoline station as claimed in claim 5, wherein the specific steps of receiving the real-time image of the fuel discharge area of the gasoline station vehicle and detecting whether the fuel discharge area of the gasoline station vehicle contains the illegal vehicle or not by combining the preset fuel discharge time range comprise:
in the real-time image of the oil unloading area of the gas station vehicle, a preset oil unloading time range is taken as an intercepting time period, images in the period of the non-oil unloading task outside the preset oil unloading time range are reserved, when the vehicle appears in the images in the period of the non-oil unloading task, the fact that the vehicle is parked illegally is determined, and further an alarm is given out.
7. The digital supervision method for the oil unloading process of the filling station as claimed in claim 1, characterized in that before the step S1, the method further comprises the steps of:
the method comprises the steps that field personnel log in and apply for oil discharge operation through mobile phone apps, and the login account and the password are newly added in a preset user login interface, oil discharge information is created in a preset oil discharge task interface, oil discharge tasks are newly added in a preset task list interface, and all historical oil discharge tasks and corresponding states are inquired.
8. The digital supervision method for the fuel discharge process of the fuel filling station as claimed in claim 7, wherein the fuel discharge information comprises fuel discharge time, fuel discharge state, license plate numbers before and after the fuel discharge vehicle, driver identity information of the fuel discharge vehicle and safety personnel identity information of the fuel filling station.
9. A digital supervision system for the oil discharge operation process of a gas station is characterized by comprising an information supervision unit before oil discharge operation and an information supervision unit in the oil discharge operation; wherein,
the pre-oil-discharge operation information monitoring unit is used for receiving the real-time images of the oil-discharge vehicles before the oil-discharge operation of the gas station and the real-time images of all the specified objects except the oil-discharge vehicles, detecting whether the oil-discharge operation is ready or not by combining a preset automatic identification model group, and further sending an oil-discharge operation command to field personnel after detecting that the oil-discharge operation is ready; the specified target object comprises an electrostatic identification, a fire-fighting device, an oil discharge port cover and an oil discharge pipeline;
the oil unloading operation middle information monitoring unit is used for receiving the real-time operation images of the field personnel, receiving the real-time images of the specified target objects in the oil unloading operation after the oil unloading operation task is determined to be started according to the real-time operation images of the field personnel, further utilizing the preset automatic identification model group to perform follow-up analysis on the received real-time images of the specified target objects in the oil unloading operation, and determining whether the oil unloading operation is safe or not according to the analysis result.
10. The system as claimed in claim 9, wherein the real-time images of the oil-discharge vehicles before the oil-discharge operation of the gas station and the real-time images of the other designated objects, and the real-time images of the field personnel during the oil-discharge operation of the gas station, the real-time images of the oil-discharge vehicles and the real-time images of the other designated objects are acquired by a plurality of cameras installed around the gas station.
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